Like holding hands with the person you love, happiness is a simple unforgetable moment in our lives. But is everyone experiencing happiness the same or drastically different?
With the technology that can help us understand how people describe their happiness, we present the following analysis to visualize and understand the science behind happiness by using deeper NLP methdologies in positive psychology. I want to specially thank Arpita Shah and Tian Zheng for providing coding resources for this R notebook.
Happiness is when what you think, what you say, and what you do are in harmony. —Gandhi
This project happily unites science and art. The study of happiness is an area of positive psychology that studies the factors that sustain people’s happiness in their lives. What are some factors we can associate ourselves with when we are study the science about happiness? Is it money? Is it marital status? Or is it material belongings?
Asai et al (2018) proposed a data set and outlines a few NLP problems that can be studied with. HappyDB is a corpus of 100,000 crowd-sourced happy moments via Amazon’s Mechanical Turk. Please refer to Asai et al (2018) which can be accessed on https://arxiv.org/abs/1801.07746. We explore this data set and try to answer the question, “What makes people happy?”
This section we dive into the analysis and technical part of the project.
Let us take a quick preview of what the data set looks like.
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